1. Field of the Invention
This invention relates to a physical random number generator, a method of generating physical random numbers and a physical random number storing medium. More, particularly, this invention relates to a physical random number generator, a method of generating physical random numbers and a physical random number storing medium that are applicable to a wide field ranging from general purpose computers to such a civil life level as personal computers, game machines, etc.
2. Description of the Related Art
Physical random numbers are those random numbers prepared utilizing random phenomena of the physical world, and as representative random phenomena, generation of radiation, fluctuation of thermal noises and the like are pointed out.
A conventional physical random number generator measures interval of generation or frequency of generation of random pulses generated from noise sources using radiation and thermal noise as noise sources.
For instance, when the numbers of radiation generated per unit time are measured repeatedly and a frequency distribution of measured values is prepared, it becomes close to the normal distribution of an average N and a standard deviation N.sup.1/2. That is, when the measurements are made 100 times, the measured values in 99 times will fall in the range from N-3N.sup.1/2 to N+3N.sup.1/2. Since the frequency distribution of measured values is the normal distribution, they are usable directly as normal distribution random numbers; however, a uniform distribution is generally convenient in many cases and it is necessary to convert the normal distribution into uniform random numbers.
So, in order to obtain uniform random numbers from the normal distribution, a conventional physical random number generator uses only lowest digit values of the measured results to generate random numbers that are not depending on the frequency distribution shape. Further, by using one bit value as the lowest digits of obtained measured values, the measured result can be divided into two categories: an even number or an odd number, and if the number N of generations is sufficiently large, respective generating frequency thereof becomes 50% and the character as random numbers is improved.
On a conventional physical random number generator, multi-bit random numbers are generated by providing a plurality of such one bit random number data generating circuits. Such prior art is set forth in, for instance, "Monte Carlo Method and Random Numbers" written by Mr. Shoji Ishida (Scientific Basic Theory Study, 17. 2. 29 (1965)) and the like.
However, such a conventional uniform physical random number generating method as described above has a problem that in order to obtain random number data from counted noise signals, N (100-200) noise signals must be counted, and therefore, much time is required to generate one random number.
Further, as random number data that can be generated from one noise source as a result of the above-described counting is of one bit, in order to generate random number data of byte unit which is the minimum unit that is handled by a computer, 8 non-correlative noise sources and 8 systems of random number generating circuits become necessary. This is a problem that must be solved for achieving a physical random number generator which is small in size and cheap in price.
Because of such problems, when a large scaled simulation is to be performed using random number data generated from a physical random number generator, even when a very high-speed CPU is mounted in a computer, as a time to obtain the result of computation depends on random number generating speed, it is not possible to achieve the high speed simulation.
Further, as 8 system noise sources and processing circuits are required to generate one-byte random numbers, the conventional physical random number generator is large scaled, and this is the factor that impedes the achievement of a low priced physical random number generator and the spread use thereof.
On the other hand, it is considered that if a high-speed and cheap priced physical random number generator is realized, it will be widely used not only in the field of scientific technical computation of, such as simulation, research relative to intelligence and study of security on a network, and in the field of communication equipments such as security of communication data, encoding of the modulation, and the like, but also in the field of such game machines as a probability for getting balls in pin-ball game machines, general game machines and the like.